The present invention relates to an object tracking technique capable of tracking an object in a stable manner even when the images of respective objects such as persons and vehicles intersect with one another, are hidden by one another, or even in the case that there is adverse influence of external disturbance such as noise received by the imaging apparatus due, for example, to environmental changes.
As for related object tracking techniques, there is one method for tracking an object as follows: Templates such as texture patterns of respective objects are previously stored, and a search operation is carried out within an image frame using these templates; the region within the image frame that resembles the template most is considered to be the position to which an object has moved within the image frame; this operation is repeatedly carried out with respect to a stream of input frames so as to track the relevant object. Also, there is another object tracking method (refer to in non-patent publication 1). That is, even in the case that a plurality of objects appear in the image and the images of respective objects intersect one another, a template matching operation is carried out based upon templates which correspond to the respective objects; the objects are tracked in a continuous manner before the images of plural objects intersect one another, and also after the images of plural objects intersect with one another.
Also, when tracking objects, one may use a dynamic filter, for instance, a method for tracking an object may employ a Kalman filter (refer to non-patent publication 2).
Further, when tracking an object, one may use a weighting coefficient(refer to patent publication 1). That is, in the case that a dynamic filter, or the like is employed, a weighting coefficient is applied with respect to past input values, such that an object can be tracked while suppressing the adverse influence caused by external disturbances such as noise, observation noise.
[Non-Patent Publication 1]
W4: real-time surveillance of people and their activities Haritaoglu, I.; Harwood, D.; Davis, L. S.; Pattern Analysis and Machine Intelligence, IEEE Transactions on Volume 22, Issue 8, August 2000, Page(s): 809-830
[Non-Patent Publication 2]
Segmentation and tracking of multiple humans in complex situations Tao Zhao; Nevatia, R.; Fengjun Lv; Computer Vision and Pattern Recognition, 2001, CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on Volume 2, 2001, Page(s): 11-194-11-201 vol.2[patent publication 1]
Japanese Laid-open Patent Application No. 2005-141687 (FIG. l)